Prediction

How will your team do in the first qualifying matches for Euro 2016?

Dr Nicolas Scelles

Posted: September 2, 2014

During the World Cup, I suggested two models to explain scores of national men’s football team games based on matches from August 2012 to December 2013. The first model was based on 13 variables: population, GDP per capita, climate, experience, percentage of players, player quality, foreign managers, technology transfer through managers, home advantage, prize, prize difference in favour of the favourite, prize difference in favour of the underdog, no prize. The second model was based on home advantage and dummies for every team (1 when a team plays at home, -1 when a team plays away).

So as to propose predictions for the UEFA Euro 2016 qualifiers, Wladimir Andreff and I applied the same models in taking into account only European national teams. For the first model, we also compared real scores and those provided by the model. Thus, we calculated the average gap per game for every team that we included then so as to correct the model. From August 2012 to December 2013, the 10 over performing teams were Bosnia and Herzegovina (+1.58), Ukraine (+0.79), Liechtenstein (+0.75), Finland (+0.73), Belgium (+0.64), Iceland (+0.625), Netherlands (+0.54), Armenia and Israel (+0.5), and Ireland (+0.47). The 11 underperforming teams were San Marino (-1.2), Turkey (-0.76), Slovakia (-0.75), Georgia (-0.58), Latvia (-0.54), Croatia (-0.533), Norway (-0.529), Wales (-0.5), and Denmark and Italy (-0.44). 6 teams performed in average as predicted by the model: Czech Republic, England, Kazakhstan, Russia, Slovenia and Spain.

Here are our predictions for match day 1 (7, 8 and 9 September):

Home

Away

Model 1

Model 1 corrected

Model 2

Denmark

Armenia

1.51

0.57

0.59

Georgia

Ireland

-0.19

-1.25

-0.81

Hungary

Northern Ireland

1.15

1.15

0.54

Faroe

Finland

-1.93

-2.74

-2.01

Greece

Romania

0.40

0.92

0.95

Germany

Scotland

1.96

2.10

2.54

Gibraltar

Poland

-4.48

-4.08

-4.381

Portugal

Albania

0.86

1.37

1.61

Serbia

France

-0.57

-0.496

-0.37

Russia

Liechtenstein

4.11

3.36

3.495

Austria

Sweden

0.12

0.49

0.31

Montenegro

Moldova

0.63

0.97

1.16

Luxembourg

Belarus

-1.01

-1.33

-1.29

Spain

Macedonia

2.14

2.02

2.19

Ukraine

Slovakia

0.68

2.21

1.37

Estonia

Slovenia

-0.31

-0.37

-0.96

San Marino

Lithuania

-1.85

-2.98

-3.93

Switzerland

England

-0.85

-0.68

-0.20

Kazakhstan

Latvia

-0.08

0.46

0.59

Azerbaijan

Bulgaria

-0.22

-0.29

-0.15

Croatia

Malta

1.71

1.58

2.86

Norway

Italy

-1.10

-1.19

-0.69

Czech Republic

Netherlands

0.04

-0.496

-1.14

Iceland

Turkey

-1.57

-0.18

0.26

Andorra

Wales

-2.44

-1.63

-2.33

Bosnia & Herzegovina

Cyprus

1.42

3.23

3.44

Israel

Belgium2

-0.58

-0.72

-1.07

1Given that Gibraltar did not play in the past, we arbitrarily chose to allocate San Marino’s coefficient to Gibraltar.

2 Israel-Belgium has been postponed and will be played on March 31, 2015.

Surprising outcomes are obviously not excluded: in June 2013, Armenia won 4-0 in Denmark whereas our models predict a Danish success. Consequently, as for the World Cup, take care before betting on the basis of our predictions!

About Dr Nicolas Scelles

Nicolas Scelles is a Lecturer at the School of Sport, Stirling University, Scotland. He holds a PhD in sports economics from the University of Caen Basse-Normandie, France. He has articles in international journals including Applied Economics, Economics Bulletin, International Journal of Sport Finance and International Journal of Sport Management and Marketing.